A sale consummates at a retail store when a customer accepts the price set by the retailer, for example, grocery at Safeway or merchandise at Sears. Retailers at different locations usually set different prices for the same commodity, for example gas at Shell stations or hamburger at McDonald's. Different prices arise also in retail markets where bargaining over price is permissible. Additionally, volume discount is not uncommon in both retail and wholesale businesses. The mainstream neoclassical economic theory informs that a commodity's value in terms of price is not unique but varies with the circumstances reflecting buyers' demand and a supplier's cost.
The same commodity may still have another price if its sale is conducted through auction. Price of an auction would similarly depend on where and when the auction is held, and who are the bidders. Moreover, different auction rules will result in different prices. In the common English auction ascending bids are heard through oral outcry and the person outbids everyone else wins. In contrast, Dutch auction is conducted in descending price and the one who first cries out wins. The more recent Vickery auction, on the other hand, allows the highest bidder to pay at the price of the second highest bid. Incentive problem and informational asymmetry are the reasons why prices would be different under different auction rules.
Trading in markets of many buyers and sellers has evolved from English auction. In the trading of stocks the early call-through system had an auctioneer who was only a market maker. As it further developed into an open-board system, there emerged specialists who not only performed a market-making role but also made profits by buying and selling out of own accounts. As a result, the listed stocks on NYSE or NASDAQ have a bid price and an ask price. The spread between bid and ask prices is eventually distributed among specialists, brokers, or order routing companies. However, such market of many buyers and sellers has a drawback. Whereas customers in retail sales or auctions would know exactly their transaction prices before deals are reached, a stock investor does not know the resulting transaction price before his/her market order is filled. Furthermore, neither NYSE nor NASDAQ provides real-time public information about the exact transaction prices established by specialists or market makers. The investors would only know from public information the bid and ask quotes, and a commitment from the Securities and Exchange Commission (SEC) to enforce best price principle. The price spread therefore leaves room for misconduct. William Christie and Paul Schultz (1994) raised such a concern when finding that market makers in NASDAQ did not quote in odd-eighths. In response, the SEC launched a full investigation and issued Order Handling Rules in August 1996. NASDAQ's minimum quotation increment was then reduced from ⅛ of a dollar to 1/16.
Recent technological innovations have shown significant impacts on the trading of goods, services, and financial instruments. The Internet connection of geographically dispersed consumers and investors has enabled immense market areas. Many retailers now have web sites to handle orders through electronic catalogs. For instance, Amazon.com becomes a major online retailer in books with the whole world its customer base. Similarly eBay.com enables global auctions by consumers and small businesses. The two examples of e-commerce, however, show a single universal sale price for an item sold. With immense market made possible by Internet technologies, different prices reflecting local demand and supply conditions seem to be at the danger of disappearance. Priceline.com provides, however, an innovative alternative. Using the invention disclosed in U.S. Pat. No. 5,794,207, the web site makes available online a variant of Dutch auction for a buyer to name his/her price. Multiple prices of an airline ticket, for example, that can meet various local demands are therefore brought back to e-commerce.
There have been many technological advances applied to securities market since late 1960s. We do not review here prior art related to quotation dissemination, order routing, trade comparison, or online trading. We instead concentrate on prior art related to matching systems (also known as automated crossing networks).
The use of computers to facilitate stock price negotiation and match between buyers and sellers was first disclosed in U.S. Pat. No. 3,573,747. The Instinet system today pairs buyers with sellers on a time priority basis. For exchange-listed issues orders are executed at the closing price, whereas over-the-counter issues are priced at the midpoint of the inside market. A computation system was disclosed in U.S. Pat. No. 3,581,072. The system accepts limit orders and market orders, and executes all orders where a bid price is at or greater than an offer price. Simulating the open-board stock trading, U.S. Pat. No. 4,412,287 discloses an automated stock exchange where a computer matches buying and selling orders for a variety of stocks and for any size. U.S. Pat. No. 4,674,044 discloses an automated security trading system that provides improved data processing and enables inventory control and profit accounting for market makers. Liquidity to securities markets was considered in an automated system disclosed in U.S. Pat. No. 5,101,353. U.S. Pat. No. 5,136,501 discloses an anonymous matching system that additionally considered credit limits.
As William A. Lupien and John T. Rickard recently state in the detailed description part of their U.S. Pat. No. 6,012,046, “a major problem encountered in the design of crossing networks is that of determining how to match buyers and sellers.” The problem, in other words, is how to determine transaction price in matching buyers and sellers. They summarize in their patent description that there are basically three matching rules in crossing networks: the take-out rule that matches overlapping bids and offers at the midpoint of the price spread, the single price auction rule that matches buyers and bidders at a size-weighted average price from overlapping bid and offer prices, and the premium rule “where bids and offers have an associated positive or negative premium, and crossing takes place at the midpoint of market spread or at the minimum necessary premium differential from the midpoint”. Taking issues with ad hoc matching rules, they disclose an innovative matching process that maximizes joint satisfaction of all participants.
A careful examination of their maximization algorithm shows, however, that buyers and sellers are still matched at a size-weighted average price. It further shows that their maximizing algorithm is problematic. First, the mutual satisfaction density defined as the multiplicative product of or the minimum between two individuals' satisfaction densities is not meaningful. Consider the case where individuals A, B, C's satisfaction densities for a given price and size are 0.3, 0.4, and 0.5, respectively. Economists have long elucidated that individual's utility, satisfaction density as used by Lupien and Rickard, is only ordinal in nature and cannot be interpersonally compared. There is no way to infer that C's satisfaction is greater than B's, B's greater than A's, or C's greater than A's. Therefore, it's not true that the mutual satisfaction density of 0.15 (or 0.3 by their minimum definition) between A and C indicates a higher mutual satisfaction than that of 0.12 (or 0.3) between A and B. Second, it's equally meaningless to add mutual satisfaction densities of all participants and seek optimal allocations of amounts and prices through their mathematical algorithm. The reason is again that utilities or satisfaction densities cannot be added across different persons as cardinal numbers. Third, the link between the computed average price and a trader's submitted prices is weak. The mutual satisfaction between a particular buyer and a particular seller can be very low even when all participants' joint mutual satisfaction is maximized. When that happens the algorithm will in effect mismatch two parties and very likely at a computed average price that neither party has indicated in his/her satisfaction profile. In addition, though the algorithm can effectuate multiple transaction prices for a stock, the price distribution is not disclosed. These problems pose threat to traders' interests in that a better match would be lost and that it will be very difficult to ascertain whether there is computation error or misconduct in the matching process.
Recent emergence of e-marketplace or digital exchange through Internet suggests that there will be more application of Internet technologies to the trading between many buyers and sellers. Web sites such as e-Steel, CATEX, Chemdex, e-chemicals, CreditTrade, and OracleExchange are serving trading demand in various industries. These sites typically have extensive electronic product catalogs and adopt traditional auction rules. On the other hand, Lupien is partnering with a digital exchange, ShipDesk, to use his newly patented trading rule.
Yet, industry demand for the growing e-marketplace or digital exchange is not fully met by existing trading rules. It is worthwhile stressing again that the value of a commodity is uncertain, just like that of a stock. Demand fluctuations and temporary disruptions of supply are usual causes for the uncertainty. News of technological breakthrough and change in business strategies are additional causes in this era of constant change. Users, suppliers or wholesalers would have different appraisal of all these factors. The information of these value appraisals, however, is not available. A reason, as mentioned earlier, is that most trading rules only effectuate a transaction price. Another reason is that multiple transaction prices, even effectuated in some way, are not disclosed to the public. Both present problems to business management, inventory management, capacity management and risk management.
One issue related to inventory is how to account for its value and manage a proper level of inventory. Traditionally, there are first-in-first-out (FIFO) and last-in-first-out (LIFO) methods for inventory value accounting, as inventory is accumulated over time. A new way to reduce inventory cost is just-in-time production and it shows tremendous success in various industries. Yet, there is capacity management problem regarding production to order. For both cases a market effectuating multiple transaction prices of a commodity at any given time can offer additional advantage. With a price distribution of a commodity, as represented by multiple transaction prices and corresponding volumes, inventory stock becomes essentially a portfolio consisting the same commodity of high and low prices. Inventory management can therefore be conducted by value rather than time, just as the management of a portfolio of equity stocks. Similarly, adjustment of just-in-time production orders or manufacturing capacity can be better managed with information of the commodity's price distribution. It is clear as well that wholesalers need to conduct similar inventory and order management. The information of price distribution can help more efficient operations.
It should also be mentioned that financial people have long recognized the uncertainty of asset value and its associated risks. Mutual fund managers use stock portfolio to diversity risk. Market makers in stock exchanges or OTC manage a given stock of several different prices, a price portfolio as we call it below. A trading method and system that can effectuate multiple transaction prices and disclose the price distribution therefore will not only extend market's function into the discovery of a price distribution, but also enable price portfolio management in financial sector as well as manufacturing and distribution sectors.
Finally, it is worth noting that the regulation of stock exchange or OTC trading is very costly. There is cost associated with the operation of a self-regulatory body. There is also cost associated with government regulation. A primary reason for the regulation is that price spread leaves room for misconduct. Were trading rules not improved, the growing number of e-marketplaces or digital exchanges would mean that regulation cost must grow proportionally to maintain orderly markets for the new economy. There would be additional cost to individuals as well, because they need to spend more time monitoring prices in various virtual markets. The cost would be far more than proportional because time cost does not exhibit constant or decreasing feature. A need is therefore to reduce monitoring and regulation costs of digital exchanges in the Internet age.
In summary, the above review shows that there still are trading problems to be solved.                1. The spread between bid and offer prices in established stock exchanges and OTC leaves room for misconduct.        2. Crossing networks' matching rules set a transaction price in ad hoc fashions.        3. The latest related patent by Lupien and Rikard, though claimed to maximize joint satisfaction, is problematic and does not empower traders with full price transparency.        4. Investors, while can manage a portfolio of stocks to diversify risks, currently have no way to purchase or sell, at a point in time, a portfolio of a given stock with different prices and quantities. The problem is acute because the uncertainty of a stock's value cannot be directly observed and can only be inferred from daily price fluctuation. As a result, investors' rush into buying or selling when market condition changes has become a source of market volatility.        5. The growing number of e-marketplaces or digital exchanges means that horrendous regulation cost would be incurred in maintaining orderly markets in a new economy, were there no improvement on trading art.        
Therefore, an object of the present invention is to effectuate multiple transaction prices for a commodity in a market of many buyers and sellers.
Another object of the present invention is to enable direct observation of a commodity's transaction price distribution.
An additional object of the present invention is to enforce transaction prices to be always equal to the common prices submitted by both buyers and sellers for a commodity.